The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
Factors Affecting Mobile Payment Adoption Intention: An Indian Perspective
Open accessAbstract
This study aims to identify the factors affecting mobile payment (m-payment) adoption intention in India by proposing a conceptual framework based on technology acceptance model (TAM). In addition to construct of TAM, four user-centric constructs have been added to evaluate m-payment adoption intention in India. The proposed research framework was empirically tested by data collected from 381 potential m-payment service users, through online and offline survey. Data were analysed using structural equation modelling (SEM) technique. The results exhibit that perceived ease of use (PEOU), perceived usefulness (PU), trust, and self-efficacy (SE) have a significant positive impact on m-payment adoption intention. However, subjective norms (SN) and personal innovativeness (PI) have no significant impact on m-payment adoption intention. Findings of the study have important theoretical and practical implications, particularly to understand important user-centric factors affecting m-payment adoption.
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The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Principles and Practice of Structural Equation Modeling
Tabri, N., & Elliott, C. M. (2012) · Canadian Graduate Journal of Sociology and Criminology · doi:10.15353/cgjsc-rcessc.v1i1.25 · Cited by 38,891
(1975) · PhilPapers (PhilPapers Foundation) · Cited by 36,737
A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies
Venkatesh, V., & Davis, F. D. (2000) · Management Science · doi:10.1287/mnsc.46.2.186.11926 · Cited by 23,066
From Intentions to Actions: A Theory of Planned Behavior
Ajzen, I. (1985) · Action Control · doi:10.1007/978-3-642-69746-3_2 · Cited by 19,057
Qu, X. (2007) · Technometrics · doi:10.1198/tech.2007.s455 · Cited by 14,705
The use of partial least squares path modeling in international marketing
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009) · Advances in International Marketing · doi:10.1108/s1474-7979(2009)0000020014 · Cited by 10,926
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Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102144 · Cited by 820
A meta-analysis of antecedents and consequences of trust in mobile commerce
Sarkar, S., Chauhan, S., & Khare, A. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.008 · Cited by 375
Cashless Transactions: A Study on Intention and Adoption of e-Wallets
Yang, M., Mamun, A. A., Mohiuddin, M., Nawi, N. C., & Zainol, N. R. (2021) · Sustainability · doi:10.3390/su13020831 · Cited by 326
Gupta, A., Yousaf, A., & Mishra, A. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102094 · Cited by 303
QR code and mobile payment: The disruptive forces in retail
Yan, L.-Y., Tan, G. W.-H., Loh, X.-M., Hew, J.-J., & Ooi, K.-B. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102300 · Cited by 252
Metadata
- Authors
- Shankar, A., & Datta, B.
- Venue
- Global Business Review
- Publisher
- SAGE Publications
- Published
- 2018-02-28
- Volume
- 19
- Issue
- 3_suppl
- Pages
- S72-S89
- ISSN
- 0972-1509 (ISSN-L)
- 0973-0664
- OpenAlex
- W2790330631
- Cited by
- 312
- References
- 73
- FWCI
- 37.67
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
